Kartones Blog

English Vocabulary Launch: Upgrade your speaking is, as you might have guessed, about improving vocabulary. The course is from the same author of English Grammar Launch and English Grammar Launch Advanced so, as I liked them, I gave it a try.

The "joke, fact & quote" idea is not bad in theory, but the jokes are a) terrible and b) way too "deeply" explained up to the point they feel like a waste of time. The fact and the quote are better but still too much time is spent explaining them. On the other hand, the pronunciation videos (zoomed so we can see the speaker mouth move) are a really cool idea, and in general the vocabulary was interesting and I learned quite a few new words, so I recommend it.

Posted on 2019-01-29

For a change, I recently did a different Udemy course, Communication Fundamentals: How To Communicate Better.

Learning to more effectively communicate with others, specially in work environments. We get explanations and tips to detect and handle different personalities, styles of communication, being empathic, "the power of silence", among other topics. It includes a role-playing scenario acting, and some exercises to do by yourself.

My only complain is that the speaker goes quite fast across the content, even at 1x speed sometimes you have to pause to digest a slide or what was just said. On the other hand is a good way to practice english, as it is very well spoken.

The duration is 1.5 hours so, as a colleage named it, a "knowledge pill" you can quickly take and learn the basics about something without needing to spend too much time.

Posted on 2019-01-29

A while ago I read an article about implementing linked lists on Python and to practice I reproduced the same interface with some additions (adding a tail, mypy type hints and a few tests).

Then I forgot about it, until recently I read something about sorting linked lists (I think in the DOOM source code analysis book I've read but it's not relevant) and I thought "I have this Python implementation, why not practice ordering that list?", so I grabbed the code, started working on it and, apart from a bugfix (tests are wonderful but you need to do proper ones and not just happy cases), I ended up adding new functions like insert_after(), sort(), flip(), clear(), making the linked list iterable and improving some operations performance along the way (also refreshing the big-O notation).

The beauty of having spent some time iterating on adding those new functions and "enhancements" is that now the code looks so slick and still useful, as you can specify your own sorting logic, normal or reverse, etc.. Here's for example the relevant code to make the list iterable and sortable:

def __init__(self) -> None:
    self.head: Optional["LinkedListNode"] = None
    self.tail: Optional["LinkedListNode"] = None

    self._iteration_cursor: Optional[LinkedListNode] = self.head

def __iter__(self) -> "LinkedList":
    self._iteration_cursor = self.head
    return self

def __next__(self) -> LinkedListNode:
    if self._iteration_cursor:
        current_node = self._iteration_cursor
    else:
        raise StopIteration
    self._iteration_cursor = self._iteration_cursor.next_node
    return current_node

# ...

def sort(self, comparison_function: Callable, reverse: bool = False) -> None:
    ordered_list = sorted(self, key=comparison_function, reverse=reverse)

    self.clear()

    for node in ordered_list:
        self.append(data=node.data)

And a sample usage taken from the tests:

def node_comparison_function(node):
    return int(node.data["id"]) if node else 0

node_1_data = {"id": 1}
node_2_data = {"id": 2}
node_3_data = {"id": 3}
node_4_data = {"id": 4}

linked_list = LinkedList()
linked_list.append(node_1_data)
linked_list.append(node_2_data)
linked_list.append(node_3_data)
linked_list.append(node_4_data)

# 1 2 3 4 -> 4 3 2 1
linked_list.sort(comparison_function=node_comparison_function, reverse=True)

It was a nice exercise and after yesterday a friend sending me a link to Nicholas Zakas Javascript implementation of a single linked list I like how my approach is quite extensible and fast, but in exchange requires you to explicitly find the nodes before being able to remove() or insert_after(). Although having to write list.remove(list.find(xxxx)) instead of list.remove(xxxx) doesn't feels terrible to me (explicit over implicit?), and the list interface becomes more tight as uses nodes everywhere possible instead of raw data, leaving that for inserts and searches only.

All of this was just meant to say that if you want a Python double-linked list implementation quite deeply tested, type annotated, with reversing, inserting at head/tail/anywhere, searching and sorting by custom function in both directions, I built one: https://github.com/Kartones/PythonAssorted/tree/master/double-linked-list .

Posted on 2019-01-17

Last weekend I did one of those typical boring tasks you always feel too lazy to do: Checking the whole blog CSS to remove all the unused Bootstrap clutter. Some time ago I fully removed all the javascript from the site (excepting an async stats ping ajax call using vanilla js and deferred 5 seconds) and I never used comments or forms since I migrated to the blog to Pelican (almost 3 years ago), so I was expecting lots of unused stuff... but the CSS went from around 50KB minimized, to less than 15KB!

It might seem extreme, but one hobby (obsession?) that I have is to try to apply speed ups to my tiny blog to play with different techniques and tips, so achieving that small size, plus not using web-fonts (I hate the loading blinking until font is rendered and fallback fonts are a patch), keeping always the content minimized, supporting Gzip and cache expiration headers, make me feel good knowing it loads as fast as possible.

I don't apply everything I read about if is not worth it, though. As an example, deferring image loading to visible viewport is something I did in the past but the gain was so small (as I don't abuse images on posts, and many are pure text) that instead I started properly compressing images... well, really obsessively, as I applied Google's Guetzli compressor to all existing images (you can achieve around 20%-25% size saving on a JPG), so they simply load quickly. But then, with some images the size of any 85% quality exported JPG is already so small that is not worth the 2-3 minutes of Guetzli compression (at least on my old laptop), so I'm more selective now on what to squeeze and what to leave as a standard JPG.

The blog does not need it, but at my portfolio I've also inlined CSS (one less HTTP request) and the small company logos are a sprite sheet so it's also a single HTTP request instead of one per logo (plus some PNG palette reductions making the file weight ~10KB).

I also like to run "crazy" compatibility and speed tests from time to time, like browsing the blog on my Nintendo 3DS or with my Kindle (which is has to be worse and slower than most phones on Earth), just because "why not?", for fun. Browsing from an ebook reader having so powerful phones is absurd but a decent challenge.

And all of this comes to light after reading an interesting post , The Cost of Javascript In 2018, which contains lots of interesting advices on pretty actual techniques (specially if you are working with SPAs and/or modern javascript frameworks). Definetly recommended reading.

Update: Link to the great Smashing Magazine's Front-End Performance Checklist 2019, a huge article containing most if not all state-of-the-art performance improvements and tips you can apply to web applications, static resources and the like. A must read.

Posted on 2019-01-03

Review

Title: Game Engine Black Book: DOOM

Author: Fabien Sanglard

Second book from Fabien Sanglard analyzing the source code of another id Software hit, this time the awesome DOOM, released in 1993. Over more than 400 pages we get to learn about the 80486, NeXT workstations and in general hardware of those years, very relevant for the development and optimizations of the game. We of course get detailed explanations of the most relevant fragments of the source code (covering most of the engine), but an interesting newcomer for this book is a quite big section dedicated to the various console ports the game had and their "adventures".

It is amazing to learn how the 3D engine drawn based on the visplanes and the optimizations it had to do paint vertically, draw first the walls and then ceilings and floors, and multitude of internals that back then were never done before. It is also yet another example of how genius John Carmack is, when he designed a mostly multi-platform architecture so that only modifying 5 .c files the game would run on NeXT, MSDOS or other systems (today runs almost everywhere), abstracting all I/O, from VGA access to sound or input.

The following image is an example of the many diagrams (and interesting content) you will find inside, showcasing another topic I really liked: the artificial intelligence of the monsters and the "noise tricks" to simulate entity scripting.

As a retro gamer, I loved the section of the different ports of the game to consoles, with greatly detailed intros of each platform's hardware to pave the road to why most of the ports were poor than "a simple PC". Specially incredible is the story behind the Super Nintendo / Super Famicon port with the SuperFX2 chipset and reverse engineered DOOM code and data. In general, rendering 1 pixel-wide columns for consoles which were great with 3D but had no proper texture perspective correction is another clever idea I wouldn't have imagined even possible.

If DOOM became an instant classic for you either when it came out (or when you were able to have it, as for example in Spain until DOOM II came out was impossible to obtain the first one without resorting to piracy), this book is a must have read. Some concepts won't be easy to digest at first but it is both a testament of technical advancements and a small compedium of achieving the impossible (some console ports).

After first Wolfenstein 3D and now DOOM, I can only hope now that the author has the strength to write the third book about my all-time favourite, Quake :)

Posted on 2018-12-31